立体视觉神经网络定位方法

为了解决计算机视觉中摄摄像机标定存在的若干问题，根据立体视觉原理，提出了基于神经网络的测避方法，利用神经网络建立空间点世界坐标与图像坐标非线性映射关系，使系统不经过复杂的摄摄像机内外参数标定，就能将二维像坐标（输入）与三维物坐标（输出）一一对应起来，并与传统的定位方法进行了比较．实验表明，该方法有效可行，简化了视觉系统的标定和定位计算，较之传统方法更具科学性，在定位精度上达到了良好效果。

Stereovision location method based on neural networks

To solve solid seeing demarcate problems,on the basis of computer vision,a new stereovision measurement technology based on neural network is proposed.Artificial neural networks are used to learn the relationships between the image information and the 3D information.For two-cameras system,the complicated relation between the cameras is established by training the network without the parameters of the cameras calibrated.It neither requires an accurate mathematical model nor needs any prior knowledge about the parameters.The 3D information of target is achieved from network output.Experiment results verify the efficiency and simplicity of the method.The method improves the accuracy and the robustness in comparison with traditional stereovision location methods.